Langgraph RAG: Building Smarter Multi-agent Systems with Knowledge Graphs and Retrieval-Augmented Generation

By James Wiglow

This comprehensive guide dives deep into the cutting-edge world of multi-agent systems (MAS), knowledge graphs, and retrieval-augmented generation (RAG). Perfect for developers, AI enthusiasts, and professionals, this book will teach you how to design and deploy smarter AI workflows by integrating LangGraph with RAG systems for real-time data retrieval and enhanced decision-making.

Through practical examples and hands-on projects, you'll learn to:

Build and manage multi-agent systems that collaborate seamlessly to solve complex problems.Utilize knowledge graphs to represent and structure data efficiently, making it easily accessible for agents.Enhance the capabilities of language models by integrating RAG for smarter, context-aware outputs.Optimize the performance and scalability of your systems while ensuring real-time responsiveness.

From concepts and theory to advanced techniques, this book offers clear explanations and well-structured chapters designed to guide you through every step of building intelligent, scalable AI systems. Whether you're looking to integrate NLP models, develop autonomous agents, or create data-driven decision-making systems, this book provides the tools and knowledge you need to succeed.

Ideal for anyone interested in AI, LangGraph RAG will help you understand and apply state-of-the-art AI technologiesin real-world applications, from healthcare and finance to smart cities and autonomous vehicles. Dive into the future of AI and learn to build intelligent systems that think, act, and collaborate-just like humans.

• Format: Paperback
• Language: English
• ISBN: B0DTF4WNYM
• ISBN13: 9798307373729
• Release Date: January 2025
• Publisher: Independently Published
• Length: 230 Pages
• Weight: 0.89 lbs.
• Dimensions: 0.5" x 7.0" x 10.0"